Giter VIP home page Giter VIP logo

Comments (7)

DarrenWong avatar DarrenWong commented on September 15, 2024 1

Dear Dr. Zhang, thanks again for your kind support. We will consider involving clustering or integrating with learning-based detection before the fine refinement based on your pipeline. The unexpected dynamic objects are quite challenging for large-scale mapping, especially in dense urban such as Hong Kong. Hopefully, we could have a chance to collaborate on dynamic object removal in the future.

from dynamicmap_benchmark.

Kin-Zhang avatar Kin-Zhang commented on September 15, 2024

image

Thanks for sharing, I checked, it looks like you forgot to save the pose in the VIEWPOINT field: https://kth-rpl.github.io/DynamicMap_Benchmark/data/#a-header-example

And here is an example way to save (C++/python):

C++: https://github.com/Kin-Zhang/simple_ndt_slam/blob/e12840886641b364580f9b5820164b8b849d7899/tools/src/extract_pcdFbag_tf.cpp#L195-L203

      // set the viewpoint -> CHECK PCD VIEWPOINT FIELD
      pcl_cloud->sensor_origin_ = Eigen::Vector4f(pose[0], pose[1], pose[2], 0.0); 
      pcl_cloud->sensor_orientation_ = Eigen::Quaternionf(pose[6], pose[3], pose[4], pose[5]); // w, x, y, z


      // save the pcd
      std::ostringstream tmp_filename;
      tmp_filename << save_pcd_folder << "/pcd/" << std::setfill('0') <<
      std::setw(6) << count << ".pcd"; std::string pcd_file =
      tmp_filename.str(); pcl::io::savePCDFileBinary(pcd_file, *pcl_cloud);

In python way:

# NOTE: We transform the point cloud to the world frame based on pose
pose2world = SE3(T[:3, :3], T[:3, -1])
points = np.hstack((pose2world.transform_point_cloud(points[:,:3]), points[:, 3].reshape(-1, 1)))
# // transform intensity to label as uint32_t, check semantic KITTI config file:
# // https://github.com/PRBonn/semantic-kitti-api/blob/master/config/semantic-kitti-mos.yaml#L33-L41
intensity = np.zeros_like(sem_labels, dtype=np.float32)
intensity[np.isin(sem_labels, [252, 253, 254, 255, 256, 257, 258, 259])] = 1
save_points = np.hstack((points[:, :3], intensity.reshape(-1, 1))) # [x, y, z, intensity]
save_pcd(save_pcd_file, save_points, np.array([xyz[0], xyz[1],xyz[2], qxyzw[3], qxyzw[0], qxyzw[1], qxyzw[2]]))

from dynamicmap_benchmark.

DarrenWong avatar DarrenWong commented on September 15, 2024

Thanks for your reply! I will re-implement the Pcd write part and evaluate again.

from dynamicmap_benchmark.

DarrenWong avatar DarrenWong commented on September 15, 2024

Dear Dr. Zhang,

Thanks for your reply. The results are impressive after I regenerate the pcd and put it into testing again using Dufomap. However, some areas especially on the opposite road are not good. Is it possible for you to provide some hints on any parameter I could further turn (default config of Dufomap is used)? The update data is provided for your reference. Thank you very much for your time!

The update PCD viewpoint using the SLAM pose,
image

The car near the sensor is removed
image

For the cars on the opposite road of the vehicle sensor platform has remained

image

from dynamicmap_benchmark.

Kin-Zhang avatar Kin-Zhang commented on September 15, 2024

image

I checked again and believe this is at the end of the frame, and since the DUFOMap strategy is to build the void(free) map, but the space you show and I pointed out, we don't have enough time/dense info to say that.

And this is one limitation we already mentioned in the paper Sec V-E:

image

from dynamicmap_benchmark.

DarrenWong avatar DarrenWong commented on September 15, 2024

Thanks for your reply!

from dynamicmap_benchmark.

Kin-Zhang avatar Kin-Zhang commented on September 15, 2024

No worry. Let me know if you have any further questions.

from dynamicmap_benchmark.

Related Issues (17)

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. 📊📈🎉

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google ❤️ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.